Pitfalls in studying “big data” from operational scenarios

Ortiz, Estefan; Bowyer, Kevin W.

doi:10.1109/btas.2016.7791194

Cited by 3 publications

(13 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…By the design, this dataset is biased toward better performing users, as it contains mainly the data from travellers who did not experience problems with the system and does not contain any rejected transactions. Nevertheless, even with this limitation, this dataset presents a unique and very valuable source for investigation of iris biometrics properties and limitations, specifically related to age and ageing, which becomes particularly important now with iris modality becoming increasingly used in many government and United Nations programmes [11, 12] and the ongoing debate related to the tolerance of iris biometrics to ageing [3–9, 13–21].…”

Section: Nexus System Descriptionmentioning

confidence: 99%

“…The OPS‐XING dataset, a part of which was used in the IREX VI evaluation by NIST [2, 4] and the evaluations conducted by UND [5, 6, 9], consists of over a quarter billion of matching and IQ metrics that were recorded during enrolment and passage transactions by the NEXUS system. These metrics are listed in Table 1.…”

Section: Ops‐xing Datasetmentioning

confidence: 99%

“…These metrics are listed in Table 1. The metrics that were shared with NIST and UND and used in the previous research [2–9] are marked in bold.…”

Section: Ops‐xing Datasetmentioning

confidence: 99%

“… Metrics used in the previous work [2–9] are marked in bold. The distributions of metric values are shown in Fig.…”

Section: Ops‐xing Datasetmentioning

confidence: 99%

“…In 2012, a portion of anonymised NEXUS kiosk log data was shared with the National Institute of Standard and Technology (NIST) scientists for the IREX VI study aimed at investigating the effect of aging on iris performance [2], where it was labelled the OPS‐XING dataset. The results of IREX VI study, which were published in 2013, brought a lot of attention from the scientific community, actively discussed and contested by the scientists from the University of Notre Dame [3–9].…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Analysis of the effect of ageing, age, and other factors on iris recognition performance using NEXUS scores dataset

Gorodnichy¹,

Chumakov²

2018

IET biom.

View full text Add to dashboard Cite

The historical NEXUS iris kiosks log dataset collected by the Canada Border Services Agency from 2003 to 2014 has become the focus of scientific attention due to its involvement in the iris ageing debate between the National Institute of Standard and Technology and the University of Notre Dame researchers. To facilitate this debate, this study provides additional details on how this dataset was collected, its various properties and irregularities, and presents new results related to the effect of ageing, age, and other factors on the system performance obtained using the portions of the dataset that have not been previously analysed. In doing that, the importance of conducting subject-based performance analysis, as opposed to the traditionally done transaction-based analysis, is emphasised. The significance of factor effects is examined. Recommendations on further improvement of the technology are made.

show abstract

Section: Nexus System Descriptionmentioning

confidence: 99%

Section: Ops‐xing Datasetmentioning

confidence: 99%

“…These metrics are listed in Table 1. The metrics that were shared with NIST and UND and used in the previous research [2–9] are marked in bold.…”

Section: Ops‐xing Datasetmentioning

confidence: 99%

“… Metrics used in the previous work [2–9] are marked in bold. The distributions of metric values are shown in Fig.…”

Section: Ops‐xing Datasetmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Analysis of the effect of ageing, age, and other factors on iris recognition performance using NEXUS scores dataset

Gorodnichy¹,

Chumakov²

2018

IET biom.

View full text Add to dashboard Cite

show abstract

Iris Recognition Performance in Children: A Longitudinal Study

Das

Holsopple

Rissacher

et al. 2021

IEEE Trans. Biom. Behav. Identity Sci.

View full text Add to dashboard Cite

Iris Recognition Performance in Children: A Longitudinal Study

Das,

Holsopple,

Rissacher

et al. 2021

Preprint

View full text Add to dashboard Cite

There is uncertainty around the effect of aging of children on biometric characteristics impacting applications relying on biometric recognition, particularly as the time between enrollment and query increases. Though there have been studies of such effects for iris recognition in adults, there have been few studies evaluating impact in children. This paper presents longitudinal analysis from 209 subjects aged 4 to 11 years at enrollment and six additional sessions over a period of 3 years. The influence of time, dilation and enrollment age on iris recognition have been analyzed and their statistical importance has been evaluated. A minor aging effect is noted which is statistically significant, but practically insignificant and is comparatively less important than other variability factors. Practical biometric applications of iris recognition in children are feasible for a time frame of at least 3 years between samples, for ages 4 to 11 years, even in presence of aging, though we note practical difficulties in enrolling young children with cameras not designed for the purpose. To the best of our knowledge, the database used in this study is the only dataset of longitudinal iris images from children for this age group and time period that is available for research.

show abstract

Pitfalls in studying “big data” from operational scenarios

Cited by 3 publications

References 7 publications

Analysis of the effect of ageing, age, and other factors on iris recognition performance using NEXUS scores dataset

Analysis of the effect of ageing, age, and other factors on iris recognition performance using NEXUS scores dataset

Iris Recognition Performance in Children: A Longitudinal Study

Iris Recognition Performance in Children: A Longitudinal Study

Contact Info

Product

Resources

About